PROJECT SUMMARY/ABSTRACT Kidney stones are common, costly, and painful, and may lead to the development of many chronic diseases. Despite advances delineating mechanisms of kidney stone formation and identifying risk factors, little has changed in the evaluation and management of the patient in the kidney stone prevention clinic during the last 20 years. Furthermore, kidney stone recurrence rates remain stubbornly high. The goal of our proposed studies is to provide new insights into the pathogenesis of stone formation that eventually will lead to the development of new treatment and/or prevention strategies. We propose to leverage the resources of the Nurses' Health Study II (NHS II) and the Health Professionals Follow-up Study (HPFS), ongoing cohort studies with decades of follow-up and rich dietary, lifestyle, and biorepository data, to conduct the first large-scale population based study (N = 800) of the intestinal microbiome and kidney stones (Aim 1), and to perform the first prospective, plasma and urine metabolomics- based study (N = 1200) of kidney stone formation (Aim 2). Intestinal microbiota may play a role in kidney stone formation by altering the absorption and subsequent urinary excretion of a wide variety of lithogenic factors. A small study reported a distinct gut microbiome in stone formers compared with controls. However, it is unknown whether differences in intestinal flora contribute to stone formation or instead represent microbial `markers' of established kidney stone risk factors such as diet and body size. In our case-control study in Aim 1, we will use stool samples from NHS II to define the intestinal microbial taxonomic and metagenomic functional ecologies in individuals with nephrolithiasis, independent of diet and body size. We also will examine associations between the intestinal microbiome and 24-hour urine composition. In prospective, nested case-control studies within NHS II and HPFS (Aim 2), we will use state-of-the-art liquid or gas chromatography followed by mass spectrometry platforms to identify > 1300 metabolites from plasma and urine. In targeted metabolomic analyses, we will identify independent associations between circulating sex hormones, microbial derived metabolites, and kidney stone risk. In untargeted metabolomic analyses, we seek to discover novel metabolite signatures associated with kidney stone formation. We will use principal component analysis and other advanced statistical methods to build distinct metabolite signatures that use all the measured plasma and urine metabolite data to distinguish kidney stone cases from controls.